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Found 12 papers, 0 papers with code
Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
Furthermore, PFL systems can also deploy both server-end and client-end defense mechanisms to strengthen the barrier against backdoor attacks.
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications
Ensemble defenses, are widely employed in various security-related applications to enhance model performance and robustness.
TBDetector:Transformer-Based Detector for Advanced Persistent Threats with Provenance Graph
APT detection is difficult to detect due to the long-term latency, covert and slow multistage attack patterns of Advanced Persistent Threat (APT).
DI-AA: An Interpretable White-box Attack for Fooling Deep Neural Networks
In this paper, we propose an interpretable white-box AE attack approach, DI-AA, which explores the application of the interpretable approach of the deep Taylor decomposition in the selection of the most contributing features and adopts the Lagrangian relaxation optimization of the logit output and L_p norm to further decrease the perturbation.
AppQ: Warm-starting App Recommendation Based on View Graphs
In this work, we propose AppQ, a novel app quality grading and recommendation system that extracts inborn features of apps based on app source code.
IWA: Integrated Gradient based White-box Attacks for Fooling Deep Neural Networks
To further make the perturbations more imperceptible, we propose to employ the restriction combination of $L_0$ and $L_1/L_2$ secondly, which can restrict the total perturbations and perturbation points simultaneously.
Generalizing Adversarial Examples by AdaBelief Optimizer
Recent research has proved that deep neural networks (DNNs) are vulnerable to adversarial examples, the legitimate input added with imperceptible and well-designed perturbations can fool DNNs easily in the testing stage.
The NiuTrans Machine Translation Systems for WMT19
We participated in 13 translation directions, including 11 supervised tasks, namely EN↔{ZH, DE, RU, KK, LT}, GU→EN and the unsupervised DE↔CS sub-track.
Bidirectional RNN-based Few-shot Training for Detecting Multi-stage Attack
"Feint Attack" is simulated by the real attack inserted in the normal causal attack chain, and the addition of the real attack destroys the causal relationship of the original attack chain.
The NiuTrans Machine Translation System for WMT18
This paper describes the submission of the NiuTrans neural machine translation system for the WMT 2018 Chinese ↔ English news translation tasks.
Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding
In addition, we propose Gradient Band-based Adversarial Training, which trained with a single randomly choose dominant adversarial example without taking any modification, to realize the "1:N" attack immunity for generalized dominant adversarial examples.
CreditCoin: A Privacy-Preserving Blockchain-Based Incentive Announcement Network for Communications of Smart Vehicles
The vehicular announcement network is one of the most promising utilities in the communications of smart vehicles and in the smart transportation systems.
